title: Combining Bayes classification and point group symmetry under Boolean framework for enhanced protein quaternary structure inference.
abstract: Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces ≥90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.
authors.affiliation: Bioinformatics Centre, Supercomputer Education Research Centre, Indian Institute of Science, Bangalore 560 012, India.
authors.forename: Pralay
authors.initials: P
authors.lastname: Mitra
authors.forename: Debnath
authors.initials: D
authors.lastname: Pal
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003460:Crystallization; D018360:Crystallography, X-Ray; D006801:Humans; D008958:Models, Molecular; D020836:Protein Structure, Quaternary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D011506:Proteins